I agree, it’s not often considered a systems programming language and it may not be the perfect tool here.
However, it is worth mentioning that cgo
Can serve as a escape hatch depending on the use case.
I agree, it’s not often considered a systems programming language and it may not be the perfect tool here.
However, it is worth mentioning that cgo
Can serve as a escape hatch depending on the use case.
Ah my bad, didn’t read.
Odin is a nice choice then, beef is another small bespoke language.
There is also zig, Go and Rust.
No language is perfect, but those languages have some features that are nice.
Windows may be easier for games, they’re exclusively written for Microsoft so that’s to be expected ( although Valve has done a lot here).
Generally speaking, modern distributions like Fedora will be no more difficult than Windows or Mac. The important distinction is that it will be different.
Microsoft has spent a lot of effort putting their operating system into every single school and business on the face of the Earth and as a result many have decades of training with that OS. That doesn’t mean their operating system is better or easier. It just means it’s familiar. If you used Android for two decades and then picked up an iPhone, I’m sure that would be just as difficult.
In the scientific space, we’ve been using *nix systems since well before Microsoft was even around so our tooling doesn’t typically support Microsoft. For us Microsoft is more difficult because that’s the training that we have.
So, it’s not that Linux has a worse user experience per se, rather it provides a different user experience. Some may consider shell scripts worse than control panel, but that’s a preference. One isn’t worse than the other. They are just different.
In my opinion:
The difference is in work, If your workflow is heavily Microsoft focused, Is a truly awful experience and you’ll feel like a second-class citizen. But if you’re working on technical things, the inverse is true, eg
For document production:
pandoc
Finally, it’s not really fair to lump all the next distributions into the same bucket, Is over 1,000 distributions and they are all quite different, Only common element is the kernel.
Gentoo is very technical but it’s also very interesting, Arch is similar. Fedora OTOH we’ll usually walk out of the box And you have your choice of desktop environment with Good support for alternative window managers like sway/Hyprland etc.
Perhaps you’re simply more familiar with Microsoft / Apple, maybe it’s not more difficult?
I too use Linux for work, but I have limited experience on Microsoft systems and have been on Linux based systems for over a decade. For me windows is a chore.
In my opinion, it’s a matter of perspective and experience. Yours is aligned with something different, that’s all.
Couldn’t agree more.
Important benefits include:
Can be viewed with visidata
Perhaps another perspective is where to draw the line in terms of expected expertise.
The book is really good and offers a snapshot of those inner workings of the language.
For using it, LLMs (open weight and otherwise) perform very well and may fill the gap.
Use Quartz and Obsidian because it’s easy. If not mcdocs.
Have a discussion with chatGPT about a program you would like to write, use this to assist the development.
Evidence this as the source of the program. There is your re-research. It’s likely the implementation will differ substantially as well.
They might own the original program but it’s unlikely they broad concept.
Well it’s there, in one loooong print out. It’s not as bad as I’m making it out to be, however, I went back to python unfortunately.
The crucial issue with Julia, no error messages.
So I use Julia for things that need to be fast (e.g. moving hdf5 to SQL and ffts) but I use python for everything else (except ggplot).
Simply, the lsp is far less useful. An object might have a dozen methods that act like verbs or some attributes that act as adjectives.
In Julia there is a huge number of functions, that work differently for different types and different combinations of types. So finding the documentation involves finding the right name for a function that does different things for different types, then scrolling down the docs for the the behaviour that corresponds to the specific combination of inputs.
I moved from R/Py to Julia for a while before moving back to Py (and a little bit of Rust).
I love how fast Julia is and the 1-index is fine for me, but I still prefer py for the oop.
Who cares if it’s European sounding, it’s still an interesting language that is relatively easy to learn, even for people from non-romance backgrounds.
I personally find multiple dispatch far more challenging to use than OOP. I’d reach for Torch over Flux any day.
Although, I really like that the majority of the Flux stack is Julia rather than a collection of Cpp.
I found reading through the rust book was a nice walkthrough of problems one can hit and how that language elected to solve them.
In terms of practice: